{"id":"https://openalex.org/W2545793358","doi":"https://doi.org/10.1109/ccis.2012.6664555","title":"A Self-learning algorithm for predicting bus arrival time based on historical data model","display_name":"A Self-learning algorithm for predicting bus arrival time based on historical data model","publication_year":2012,"publication_date":"2012-10-01","ids":{"openalex":"https://openalex.org/W2545793358","doi":"https://doi.org/10.1109/ccis.2012.6664555","mag":"2545793358"},"language":"en","primary_location":{"id":"doi:10.1109/ccis.2012.6664555","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis.2012.6664555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100526495","display_name":"Jian Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jian Pan","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043493892","display_name":"Xiuting Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiuting Dai","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061224234","display_name":"Xiaoqi Xu","orcid":"https://orcid.org/0000-0001-6304-4666"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoqi Xu","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100382117","display_name":"Yanjun Li","orcid":"https://orcid.org/0000-0002-3976-3828"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanjun Li","raw_affiliation_strings":["College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100526495"],"corresponding_institution_ids":["https://openalex.org/I55712492"],"apc_list":null,"apc_paid":null,"fwci":0.9736,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.81958729,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1112","last_page":"1116"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9915000200271606,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9563999772071838,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7360985279083252},{"id":"https://openalex.org/keywords/arrival-time","display_name":"Arrival time","score":0.6458276510238647},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6134616136550903},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.5984978079795837},{"id":"https://openalex.org/keywords/public-transport","display_name":"Public transport","score":0.4782240092754364},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46655791997909546},{"id":"https://openalex.org/keywords/time-of-arrival","display_name":"Time of arrival","score":0.4364158511161804},{"id":"https://openalex.org/keywords/travel-time","display_name":"Travel time","score":0.43598148226737976},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4163632392883301},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41475069522857666},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4085032641887665},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3531591296195984},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34122270345687866},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.21699866652488708},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.16087943315505981},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13836455345153809},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1237143874168396}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7360985279083252},{"id":"https://openalex.org/C3017552255","wikidata":"https://www.wikidata.org/wiki/Q4135208","display_name":"Arrival time","level":2,"score":0.6458276510238647},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6134616136550903},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.5984978079795837},{"id":"https://openalex.org/C539828613","wikidata":"https://www.wikidata.org/wiki/Q178512","display_name":"Public transport","level":2,"score":0.4782240092754364},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46655791997909546},{"id":"https://openalex.org/C163150518","wikidata":"https://www.wikidata.org/wiki/Q4135208","display_name":"Time of arrival","level":3,"score":0.4364158511161804},{"id":"https://openalex.org/C2985733770","wikidata":"https://www.wikidata.org/wiki/Q1233007","display_name":"Travel time","level":2,"score":0.43598148226737976},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4163632392883301},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41475069522857666},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4085032641887665},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3531591296195984},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34122270345687866},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.21699866652488708},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.16087943315505981},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13836455345153809},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1237143874168396},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccis.2012.6664555","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccis.2012.6664555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320719","display_name":"Department of Science and Technology, Ministry of Science and Technology, India","ror":"https://ror.org/0101xrq71"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W630611528","https://openalex.org/W2347989556","https://openalex.org/W2380309457"],"related_works":["https://openalex.org/W2765924402","https://openalex.org/W2920514105","https://openalex.org/W2550892593","https://openalex.org/W4387960969","https://openalex.org/W4288481730","https://openalex.org/W3003184106","https://openalex.org/W3028083027","https://openalex.org/W1581082085","https://openalex.org/W2185197683","https://openalex.org/W2999481788"],"abstract_inverted_index":{"The":[0],"provision":[1],"of":[2,23,43,86],"timely":[3],"and":[4,19,41,56,83],"accurate":[5],"bus":[6,45,55],"arrive":[7],"time":[8,62,85],"information":[9],"is":[10,33,67],"very":[11],"important.":[12],"It":[13],"helps":[14],"to":[15,78],"attract":[16],"additional":[17],"ridership":[18],"increase":[20],"the":[21,44,54,80,87,94],"satisfaction":[22],"transit":[24],"users.":[25],"In":[26],"this":[27],"paper,":[28],"a":[29],"self-learning":[30],"prediction":[31,99],"algorithm":[32,96],"proposed":[34,95],"based":[35,105],"on":[36,53,106],"historical":[37,70,107],"data":[38,71],"model.":[39],"Locations":[40],"speeds":[42],"are":[46,72],"periodically":[47],"obtained":[48],"from":[49],"GPS":[50],"senor":[51],"installed":[52],"stored":[57],"in":[58,63],"database.":[59],"Historical":[60],"travel":[61,108],"all":[64],"road":[65,88],"sections":[66],"collected.":[68],"These":[69],"trained":[73],"using":[74],"BP":[75],"neural":[76],"network":[77],"predict":[79],"average":[81],"speed":[82],"arrival":[84],"sections.":[89],"Experimental":[90],"results":[91],"indicate":[92],"that":[93],"achieves":[97],"outstanding":[98],"accuracy":[100],"compared":[101],"with":[102],"general":[103],"solutions":[104],"time.":[109]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}